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new 8e03772 [MINOR] Fix broken javadoc link in Concepts (#3270)
8e03772 is described below
commit 8e037721dfee166bcfc113da662caaa6b11d9b2d
Author: DONGYEON LEE <[email protected]>
AuthorDate: Tue May 19 03:19:30 2020 +0900
[MINOR] Fix broken javadoc link in Concepts (#3270)
---
docs/Concepts.md | 10 +++++-----
1 file changed, 5 insertions(+), 5 deletions(-)
diff --git a/docs/Concepts.md b/docs/Concepts.md
index f810d36..fd8fa88 100644
--- a/docs/Concepts.md
+++ b/docs/Concepts.md
@@ -55,9 +55,9 @@ The other main methods on spouts are `ack` and `fail`. These
are called when Sto
### Bolts
-All processing in topologies is done in bolts. Bolts can do anything from
filtering, functions, aggregations, joins, talking to databases, and more.
+All processing in topologies is done in bolts. Bolts can do anything from
filtering, functions, aggregations, joins, talking to databases, and more.
-Bolts can do simple stream transformations. Doing complex stream
transformations often requires multiple steps and thus multiple bolts. For
example, transforming a stream of tweets into a stream of trending images
requires at least two steps: a bolt to do a rolling count of retweets for each
image, and one or more bolts to stream out the top X images (you can do this
particular stream transformation in a more scalable way with three bolts than
with two).
+Bolts can do simple stream transformations. Doing complex stream
transformations often requires multiple steps and thus multiple bolts. For
example, transforming a stream of tweets into a stream of trending images
requires at least two steps: a bolt to do a rolling count of retweets for each
image, and one or more bolts to stream out the top X images (you can do this
particular stream transformation in a more scalable way with three bolts than
with two).
Bolts can emit more than one stream. To do so, declare multiple streams using
the `declareStream` method of
[OutputFieldsDeclarer](javadocs/org/apache/storm/topology/OutputFieldsDeclarer.html)
and specify the stream to emit to when using the `emit` method on
[OutputCollector](javadocs/org/apache/storm/task/OutputCollector.html).
@@ -86,7 +86,7 @@ There are eight built-in stream groupings in Storm, and you
can implement a cust
4. **All grouping**: The stream is replicated across all the bolt's tasks. Use
this grouping with care.
5. **Global grouping**: The entire stream goes to a single one of the bolt's
tasks. Specifically, it goes to the task with the lowest id.
6. **None grouping**: This grouping specifies that you don't care how the
stream is grouped. Currently, none groupings are equivalent to shuffle
groupings. Eventually though, Storm will push down bolts with none groupings to
execute in the same thread as the bolt or spout they subscribe from (when
possible).
-7. **Direct grouping**: This is a special kind of grouping. A stream grouped
this way means that the __producer__ of the tuple decides which task of the
consumer will receive this tuple. Direct groupings can only be declared on
streams that have been declared as direct streams. Tuples emitted to a direct
stream must be emitted using one of the
[emitDirect](javadocs/org/apache/storm/task/OutputCollector.html#emitDirect(int,
int, java.util.List) methods. A bolt can get the task ids of its [...]
+7. **Direct grouping**: This is a special kind of grouping. A stream grouped
this way means that the __producer__ of the tuple decides which task of the
consumer will receive this tuple. Direct groupings can only be declared on
streams that have been declared as direct streams. Tuples emitted to a direct
stream must be emitted using one of the
[emitDirect](javadocs/org/apache/storm/task/OutputCollector.html#emitDirect-int-java.util.Collection-java.util.List-)
methods. A bolt can get the [...]
8. **Local or shuffle grouping**: If the target bolt has one or more tasks in
the same worker process, tuples will be shuffled to just those in-process
tasks. Otherwise, this acts like a normal shuffle grouping.
**Resources:**
@@ -96,11 +96,11 @@ There are eight built-in stream groupings in Storm, and you
can implement a cust
### Reliability
-Storm guarantees that every spout tuple will be fully processed by the
topology. It does this by tracking the tree of tuples triggered by every spout
tuple and determining when that tree of tuples has been successfully completed.
Every topology has a "message timeout" associated with it. If Storm fails to
detect that a spout tuple has been completed within that timeout, then it fails
the tuple and replays it later.
+Storm guarantees that every spout tuple will be fully processed by the
topology. It does this by tracking the tree of tuples triggered by every spout
tuple and determining when that tree of tuples has been successfully completed.
Every topology has a "message timeout" associated with it. If Storm fails to
detect that a spout tuple has been completed within that timeout, then it fails
the tuple and replays it later.
To take advantage of Storm's reliability capabilities, you must tell Storm
when new edges in a tuple tree are being created and tell Storm whenever you've
finished processing an individual tuple. These are done using the
[OutputCollector](javadocs/org/apache/storm/task/OutputCollector.html) object
that bolts use to emit tuples. Anchoring is done in the `emit` method, and you
declare that you're finished with a tuple using the `ack` method.
-This is all explained in much more detail in [Guaranteeing message
processing](Guaranteeing-message-processing.html).
+This is all explained in much more detail in [Guaranteeing message
processing](Guaranteeing-message-processing.html).
### Tasks
